Approximation of continuous and discontinuous mappings by a growing neural RBF-based algorithm

[1]  Seongwon Cho,et al.  Self-organizing map with time-invariant learning rate and its exponential stability analysis , 1998, Neurocomputing.

[2]  N. Alberto Borghese,et al.  Hierarchical RBF networks and local parameters estimate , 1998, Neurocomputing.

[3]  Ah Chung Tsoi,et al.  Universal Approximation Using Feedforward Neural Networks: A Survey of Some Existing Methods, and Some New Results , 1998, Neural Networks.

[4]  Sujoy Ghose,et al.  Growing nonuniform feedforward networks for continuous mappings , 1996, Neurocomputing.

[5]  Stephen A. Billings,et al.  Radial basis function network configuration using genetic algorithms , 1995, Neural Networks.

[6]  Mark J. L. Orr,et al.  Regularization in the Selection of Radial Basis Function Centers , 1995, Neural Computation.

[7]  Michael A. Arbib,et al.  Generation of temporal sequences using local dynamic programming , 1995, Neural Networks.

[8]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[9]  Denise Gorse,et al.  Avoiding Local Minima by a Classical Range Expansion Algorithm , 1994 .

[10]  Thomas Martinetz,et al.  'Neural-gas' network for vector quantization and its application to time-series prediction , 1993, IEEE Trans. Neural Networks.

[11]  Jooyoung Park,et al.  Approximation and Radial-Basis-Function Networks , 1993, Neural Computation.

[12]  Bernd A. Berg,et al.  Locating global minima in optimization problems by a random-cost approach , 1993, Nature.

[13]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[14]  Kurt Hornik,et al.  Some new results on neural network approximation , 1993, Neural Networks.

[15]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..

[16]  Yoshifusa Ito,et al.  Approximation of functions on a compact set by finite sums of a sigmoid function without scaling , 1991, Neural Networks.

[17]  Robert M. Sanner,et al.  Gaussian Networks for Direct Adaptive Control , 1991, 1991 American Control Conference.

[18]  Jooyoung Park,et al.  Universal Approximation Using Radial-Basis-Function Networks , 1991, Neural Computation.

[19]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  James D. Keeler,et al.  Layered Neural Networks with Gaussian Hidden Units as Universal Approximations , 1990, Neural Computation.

[21]  Donald F. Specht,et al.  Probabilistic neural networks , 1990, Neural Networks.

[22]  John Moody,et al.  Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.

[23]  Kumpati S. Narendra,et al.  Learning automata - an introduction , 1989 .

[24]  T. Ash,et al.  Dynamic node creation in backpropagation networks , 1989, International 1989 Joint Conference on Neural Networks.

[25]  D. Broomhead,et al.  Radial Basis Functions, Multi-Variable Functional Interpolation and Adaptive Networks , 1988 .

[26]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[27]  L. Schumaker Spline Functions: Basic Theory , 1981 .

[28]  John E. Markel,et al.  Linear Prediction of Speech , 1976, Communication and Cybernetics.

[29]  R.W. Schafer,et al.  Digital representations of speech signals , 1975, Proceedings of the IEEE.